A Novel Approach Toward Algorithm Architecture Co-Optimization for the Application of Adaptive Noise Cancellation for Wireless Communication

Dr Aneela Pathan
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Abstract

As FPGA has been in trend for a few decades in prototyping simple to complex DSP systems, some issues are still highlighted in FPGA-based implementations. One issue is the limited resources mounted onboard. Optimization has always remained a choice of developers, either hardware or software-based. Algorithm architecture co-optimization is a domain that incorporates some changes in existing algorithms besides bringing some ways to produce compact architecture. One of the methods in architecture optimization is to use short-word length-based DSP systems that use a sigma-delta modulation (SDM) approach to reduce the actual data word length from multi-bit to single-bit. SDM in the design causes the system to become compact and efficient. This paper produces algorithm architecture co-optimization for the application of adaptive noise cancellers for wireless communication. The algorithm taken is SDM-based Steepest-Descent, and its implementation is compared with the new proposed SDM-based correlation-less design. Both approaches are simulated in MATLAB, and their functional verification is carried out along with comparing some statistical parameters, including SNR, MSE, and PE. Besides, both the designs are translated on Vertex-7 FPGA to verify the less resources consumed by the proposed method. The MATLAB and FPGA-based results indicate that the proposed design may be the best choice for less sensitive applications, like voice or video. 
应用自适应噪声消除技术实现算法架构协同优化的新方法
几十年来,FPGA 一直是简单到复杂 DSP 系统原型开发的趋势,但在基于 FPGA 的实现过程中仍存在一些突出问题。其中一个问题是板载资源有限。优化一直是开发人员的选择,无论是基于硬件还是基于软件。算法架构协同优化是一个领域,除了带来一些紧凑架构的方法外,还包括对现有算法的一些改变。架构优化的方法之一是使用基于短字长的 DSP 系统,该系统使用Σ-Δ调制(SDM)方法将实际数据字长度从多比特减少到单比特。设计中的 SDM 使系统变得紧凑高效。本文针对无线通信中自适应噪声消除器的应用进行了算法架构的共同优化。所采用的算法是基于 SDM 的陡升算法,并将其实现与新提出的基于 SDM 的无相关性设计进行了比较。两种方法都在 MATLAB 中进行了仿真,并在比较 SNR、MSE 和 PE 等统计参数的同时进行了功能验证。此外,两种设计都在 Vertex-7 FPGA 上进行了转换,以验证拟议方法消耗的资源更少。基于 MATLAB 和 FPGA 的结果表明,建议的设计可能是语音或视频等敏感度较低的应用的最佳选择。
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